Topical Collection "Energy Finance and Sustainable Development"

Editors

Prof. Dr. Shawkat Hammoudeh
grade E-Mail Website
Collection Editor
LeBow College of Business, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USA
Interests: energy finance; environmental economics; financial economics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Marian Siminică
E-Mail Website
Collection Editor
Department of Finance, Banking and Economic Analysis, Center for Banking and Financial Research, Faculty of Economics and Business Administration, University of Craiova, Craiova 200585, Romania
Interests: the evaluation of the economic and financial performances of the companies; the analysis of the financial risks
Prof. Dr. Ahsan Akbar
E-Mail Website
Collection Editor
International Business School, Guangzhou College of South China University of Technology, Guangzhou 510080, China
Interests: enterprise sustainability; corporate life cycle; corporate social responsibility; green investments; energy economics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Petra Poulová
E-Mail Website
Collection Editor
Department of Informatics and Quantitative Methods, Faculty of Informatics and Management, University of Hradec Kralove, 500 03 Hradec Kralove, Czech Republic
Interests: energy technologies; cloud computing; e-learning and use of technologies in healthcare

Topical Collection Information

Dear Colleagues,

Energy finance is an interdisciplinary field that brings to the attention of researchers, practitioners and other stakeholders the link between the energy market and the financial sphere (Zhang, 2018). The first concern of stakeholders has been the impact of oil prices on capital markets. Oil is an important asset that is most highly traded in commodity exchanges, in both the spot market and the derivatives segments, as well as for institutional investment (Nakajima, 2019). Investors' interest in this commodity for both speculative operation and hedging purposes has led to the financialization of the energy market. The evolution of the price of this commodity has also had a significant impact on the prices of shares traded on the stock markets. Oil prices are also priced in US dollars, and this connection has created a direct relationship between oil prices and exchange rates. For these reasons, several studies have focused on the analysis of the influence of oil prices on securities, stock indices and exchange rates for both developed and emerging market economies (Hammoudeh & Aleisa, 2004; Sari et al., 2010 among others).

On the other hand, oil companies are in the spotlight of various stakeholders, due not only to the negative externalities they generate on the environment, but also to the green-washing strategies they have initiated to improve their public image by running corporate social responsibility (CSR) programs. The sustainable development policies of firms have also garnered a favorable response from portfolio investors. Nowadays, decisions in the capital markets are taken not only according to the risk–profitability criterion, but also based on Environment, Social and Governance (ESG) performance. Thus, the trend of the divestment of securities issued by oil companies has been on the rise. Recently, portfolio investors have been more interested in environment-friendly companies, such as those that produce renewable energy (Taghizadeh-Hesary et al., 2020; Sadorsky, 2021).

Nevertheless, global warming has also generated a concerted response from public authorities and financial institutions that have launched specific tools to manage mechanisms that reduce the adverse impact of energy creation and emissions on the environment. The reduction of carbon emissions is not a simple desideratum. In order to manage the process of the transition to a low-carbon economy, emission trading schemes have been established, and the carbon market was set up. The transition to a low carbon economy is a complex and lengthy process that requires significant financial resources. The involvement of international financial organizations such as the World Bank or the International Monetary Fund (Newell, 2011) ensures the coherence of the efforts for energy transition.

The capital market offers financing alternatives to bank lending. Bonds are the tools that are already used to mobilize funds available in the economy in order finance green projects. The interest of portfolio investors in such securities is high, considering the creditworthiness of the main issuers such as the World Bank or the European Bank for Reconstruction and Development (Milford et al., 2014).

The high costs and the risks involved in certain investment projects that produce renewable energy or have a less negative impact on the environment are generating a gap between the supply and demand for financial funds. To support this process, some governments have established state investment banks (SIBs) that provide financing for green projects (Geddes et al., 2018). In China, there is extensive involvement of  the government in the energy field, through both state-owned companies and state-owned financial institutions that provide financing for the internationalization of energy companies and the financing of projects, including foreign governments (Kong, B., and Gallagher, 2017).

This call for papers will cover a variety of theoretical and empirical topics related to energy finance, taking into account the efforts that are needed to meet the Sustainable Development Goals.

The Special issue is interested in papers related, among other things, to:

  • energy finance and oil prices;
  • oil prices and climate change (is there a role for COVID-19?);
  • renewable energy and climate change;
  • energy investments, the environment and the era of sustainable globalization;
  • economic globalization and environmental degradation;
  • use of energy resources in the presence of economic globalization;
  • The Jevons paradox and the energy market, the green paradox and the energy market;
  • CSR in the oil field.

References

Geddes, A., Schmidt, T. S., & Steffen, B. (2018). The multiple roles of state investment banks in low-carbon energy finance: An analysis of Australia, the UK and Germany. Energy Policy115, 158-170.

Gopal, S., Pitts, J., Li, Z., Gallagher, K. P., Baldwin, J. G., & Kring, W. N. (2018). Fueling global energy finance: the emergence of China in global energy investment. Energies11(10), 2804.

Hammoudeh, S., & Aleisa, E. (2004). Dynamic relationships among GCC stock markets and NYMEX oil futures. Contemporary Economic Policy22(2), 250-269.

Kong, B., & Gallagher, K. P. (2017). Globalizing Chinese energy finance: the role of policy banks. Journal of Contemporary China26(108), 834-851.

Milford, L., Saha, D., Muro, M., Sanders, R., & Rittner, T. (2014). Clean Energy Finance Through the Bond Market. Brookings Institution, Brookings Rockefeller Project on State and Metropolitan Innovation.

Nakajima, T. (2019). Expectations for statistical arbitrage in energy futures markets. Journal of Risk and Financial Management12(1), 14.

Newell, P. (2011). The governance of energy finance: the public, the private and the hybrid. Global Policy2, 94-105.

Sadorsky, P. (2021). A Random Forests Approach to Predicting Clean Energy Stock Prices. Journal of Risk and Financial Management14(2), 48.

Sari, R., Hammoudeh, S., & Soytas, U. (2010). Dynamics of oil price, precious metal prices, and exchange rate. Energy Economics32(2), 351-362.

Taghizadeh-Hesary, F., & Yoshino, N. (2020). Sustainable solutions for green financing and investment in renewable energy projects. Energies13(4), 788.

Zhang, D. (2018). Energy Finance: Background, Concept, and Recent Developments. Emerging Markets Finance and Trade54(8), 1687-1692.

Prof. Dr. Shawkat Hammoudeh
Prof. Dr. Mirela Panait,
Prof. Dr. Marian Siminică
Prof. Dr. Ahsan Akbar
Prof. Dr. Petra Poulova
Collection Editors

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Keywords

  • low-carbon economy
  • carbon market
  • divestment in the fossil fuel industry
  • de-carbonization and the financial market
  • renewable energy investments
  • financialization and derivatives
  • green bonds

Published Papers (10 papers)

2022

Jump to: 2021, 2020, 2019, 2018

Article
Emissions Reduction Policies and Their Effects on Economy
J. Risk Financial Manag. 2022, 15(9), 404; https://doi.org/10.3390/jrfm15090404 - 11 Sep 2022
Viewed by 336
Abstract
The two broad carbon-reducing policies, carbon tax and cap-and-trade, have been implemented at various national and sub-national levels. This paper examines the relationships between emissions-reducing policies and their effect on the country’s economic growth (GDP) using carbon tax and CO2 emission as [...] Read more.
The two broad carbon-reducing policies, carbon tax and cap-and-trade, have been implemented at various national and sub-national levels. This paper examines the relationships between emissions-reducing policies and their effect on the country’s economic growth (GDP) using carbon tax and CO2 emission as explanatory variables and population and R&D as control variables. The study employs Granger causality analysis (GCA) and panel data regression analysis to find the relationships between GDP, emissions, and carbon tax. GDP usually increases as a country’s carbon emissions, carbon tax, R&D, and population increase. The analysis of carbon reduction policies, especially carbon tax and their general impact on a country’s economy, is a unique contribution of this study. The applications of this study are to motivate governments to form a national carbon abatement policy and encourage corporate leaders to invest in clean technology to grow the economy. Full article
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2021

Jump to: 2022, 2020, 2019, 2018

Article
The Skewness Risk in the Energy Market
J. Risk Financial Manag. 2021, 14(12), 620; https://doi.org/10.3390/jrfm14120620 - 20 Dec 2021
Viewed by 880
Abstract
In this paper, we study the skewness risk and its return predictability in the energy market. Skewness risk is often used to measure the possibility of market crash. We study both physical skewness (market skewness and cross-sectional average realized skewness) estimated from underlying [...] Read more.
In this paper, we study the skewness risk and its return predictability in the energy market. Skewness risk is often used to measure the possibility of market crash. We study both physical skewness (market skewness and cross-sectional average realized skewness) estimated from underlying stock returns and risk-neutral skewness evaluated from the options market. We find a significant positive relationship between one-month-ahead market return and average realized skewness in the energy market. This unique feature should be noted by investors and carefully considered by energy policymakers. Full article
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Article
A Random Forests Approach to Predicting Clean Energy Stock Prices
J. Risk Financial Manag. 2021, 14(2), 48; https://doi.org/10.3390/jrfm14020048 - 24 Jan 2021
Cited by 11 | Viewed by 2421
Abstract
Climate change, green consumers, energy security, fossil fuel divestment, and technological innovation are powerful forces shaping an increased interest towards investing in companies that specialize in clean energy. Well informed investors need reliable methods for predicting the stock prices of clean energy companies. [...] Read more.
Climate change, green consumers, energy security, fossil fuel divestment, and technological innovation are powerful forces shaping an increased interest towards investing in companies that specialize in clean energy. Well informed investors need reliable methods for predicting the stock prices of clean energy companies. While the existing literature on forecasting stock prices shows how difficult it is to predict stock prices, there is evidence that predicting stock price direction is more successful than predicting actual stock prices. This paper uses the machine learning method of random forests to predict the stock price direction of clean energy exchange traded funds. Some well-known technical indicators are used as features. Decision tree bagging and random forests predictions of stock price direction are more accurate than those obtained from logit models. For a 20-day forecast horizon, tree bagging and random forests methods produce accuracy rates of between 85% and 90% while logit models produce accuracy rates of between 55% and 60%. Tree bagging and random forests are easy to understand and estimate and are useful methods for forecasting the stock price direction of clean energy stocks. Full article
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2020

Jump to: 2022, 2021, 2019, 2018

Article
COVID-19 Outbreak and CO2 Emissions: Macro-Financial Linkages
J. Risk Financial Manag. 2021, 14(1), 12; https://doi.org/10.3390/jrfm14010012 - 29 Dec 2020
Cited by 7 | Viewed by 1623
Abstract
In the Dynamic Conditional Correlation with Mixed Data Sampling (DCC-MIDAS) framework, we scrutinize the correlations between the macro-financial environment and CO2 emissions in the aftermath of the COVID-19 diffusion. The main original idea is that the economy’s lock-down will alleviate part of [...] Read more.
In the Dynamic Conditional Correlation with Mixed Data Sampling (DCC-MIDAS) framework, we scrutinize the correlations between the macro-financial environment and CO2 emissions in the aftermath of the COVID-19 diffusion. The main original idea is that the economy’s lock-down will alleviate part of the greenhouse gases’ burden that human activity induces on the environment. We capture the time-varying correlations between U.S. COVID-19 confirmed cases, deaths, and recovered cases that were recorded by the Johns Hopkins Coronavirus Center, on the one hand; U.S. Total Industrial Production Index and Total Fossil Fuels CO2 emissions from the U.S. Energy Information Administration on the other hand. High-frequency data for U.S. stock markets are included with five-minute realized volatility from the Oxford-Man Institute of Quantitative Finance. The DCC-MIDAS approach indicates that COVID-19 confirmed cases and deaths negatively influence the macro-financial variables and CO2 emissions. We quantify the time-varying correlations of CO2 emissions with either COVID-19 confirmed cases or COVID-19 deaths to sharply decrease by −15% to −30%. The main takeaway is that we track correlations and reveal a recessionary outlook against the background of the pandemic. Full article
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Article
Community Participation for the Use of Renewable Energies in Ciudad Ixtepec, Oaxaca (2008–2015)
J. Risk Financial Manag. 2020, 13(8), 167; https://doi.org/10.3390/jrfm13080167 - 31 Jul 2020
Cited by 1 | Viewed by 1033
Abstract
This paper aims to examine the redefinition of rural actors and practices in the context of the Wind Farm Corridor of the Isthmus of Tehuantepec. That redefinition addresses issues such as the benefits of wind farms, the role of the land in the [...] Read more.
This paper aims to examine the redefinition of rural actors and practices in the context of the Wind Farm Corridor of the Isthmus of Tehuantepec. That redefinition addresses issues such as the benefits of wind farms, the role of the land in the use of wind energy, requirements for the use of wind, arguments of disagreement with wind farms, manifestations of that disagreement, and the feasibility of community wind farms. Adopting a case study methodology from a qualitative perspective, and “worded” data collected through semi-structured interviews, it was detected that, despite the disapproval of residents of the Oaxacan Isthmus due to a dispossession claimed to the Federal Electricity Commission (Comisión Federal de Electricidad, CFE) and private companies, many of the landowners in Ciudad Ixtepec have decided to become wind entrepreneurs by a community wind farm, facing opposition and mistrust regarding their capacities. Full article
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2019

Jump to: 2022, 2021, 2020, 2018

Article
Modeling the Impact of Agricultural Shocks on Oil Price in the US: A New Approach
J. Risk Financial Manag. 2019, 12(3), 147; https://doi.org/10.3390/jrfm12030147 - 10 Sep 2019
Cited by 11 | Viewed by 1454
Abstract
The current literature has generally considered prices of the agricultural commodity as an endogenous factor to crude oil price. As such, the role of the agricultural market in the energy sector has been largely ignored. We argue that the expansion of agricultural production [...] Read more.
The current literature has generally considered prices of the agricultural commodity as an endogenous factor to crude oil price. As such, the role of the agricultural market in the energy sector has been largely ignored. We argue that the expansion of agricultural production may trigger a significant increase in oil price. In addition, the world has recently witnessed a growth in biofuel production, leading to an increase in the size of the agricultural sector. This study is conducted to examine the impact of different agricultural shocks on the oil and agricultural markets in the US for the period from 1986 to 2018. The study utilizes the Structural Vector Autoregressive (SVAR) model to estimate the relationship between the agricultural market and the crude oil market. Moreover, the variance decomposition is also used to quantify the contribution of agricultural demand shocks on oil price variations. Findings from this paper indicate that different agricultural shocks can have different effects on oil price and that corn use in ethanol plays an important role in the impact of corn demand shocks on oil price. We find evidence that the agricultural market can have an impact on oil prices through two main channels: indirect cost push effect and direct biofuel effect. Of these, the biofuel channel unexpectedly suggests that the expansion of bioethanol may in fact foster the dependency of the economy on fossil fuel use and prices. Full article
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Article
CO2 Emissions, Energy Consumption, and Economic Growth: New Evidence in the ASEAN Countries
J. Risk Financial Manag. 2019, 12(3), 145; https://doi.org/10.3390/jrfm12030145 - 10 Sep 2019
Cited by 30 | Viewed by 2491
Abstract
The members of the Association of Southeast Asian Nations (ASEAN) have made several attempts to adopt renewable energy targets given the economic, energy-related, environmental challenges faced by the governments, policy makers, and stakeholders. However, previous studies have focused limited attention on the role [...] Read more.
The members of the Association of Southeast Asian Nations (ASEAN) have made several attempts to adopt renewable energy targets given the economic, energy-related, environmental challenges faced by the governments, policy makers, and stakeholders. However, previous studies have focused limited attention on the role of renewable energy when testing the dynamic link between CO2 emissions, energy consumption and renewable energy consumption. As such, this study is conducted to test a common hypothesis regarding a long-run environmental Kuznets curve (EKC). The paper also investigates the causal link between carbon dioxide (CO2) emissions, energy consumption, renewable energy, population growth, and economic growth for countries in the region. Using various time-series econometrics approaches, our analysis covers five ASEAN members (including Indonesia, Myanmar, Malaysia, the Philippines, and Thailand) for the 1971–2014 period where required data are available. Our results reveal no long-run relationship among the variables of interest in the Philippines and Thailand, but a relationship does exist in Indonesia, Myanmar, and Malaysia. The EKC hypothesis is observed in Myanmar but not in Indonesia and Malaysia. Also, Granger causality among these important variables varies considerably across the selected countries. No Granger causality among carbon emissions, energy consumption, and renewable energy consumption is reported in Malaysia, the Philippines, and Thailand. Indonesia experiences a unidirectional causal effect from economic growth to renewable energy consumption in both short and long run and from economic growth to CO2 emissions and energy consumption. Interestingly, only Myanmar has a unidirectional effect from GDP growth, energy consumption, and population to the adoption of renewable energy. Policy implications have emerged based on the findings achieved from this study for each country in the ASEAN region. Full article
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Article
Expectations for Statistical Arbitrage in Energy Futures Markets
J. Risk Financial Manag. 2019, 12(1), 14; https://doi.org/10.3390/jrfm12010014 - 15 Jan 2019
Cited by 8 | Viewed by 3558
Abstract
Energy futures have become important as alternative investment assets to minimize the volatility of portfolio return, owing to their low links with traditional financial markets. In order to make energy futures markets grow further, it is necessary to expand expectations of returns from [...] Read more.
Energy futures have become important as alternative investment assets to minimize the volatility of portfolio return, owing to their low links with traditional financial markets. In order to make energy futures markets grow further, it is necessary to expand expectations of returns from trading in energy futures markets. Therefore, this study examines whether profits can be earned by statistical arbitrage between wholesale electricity futures and natural gas futures listed on the New York Mercantile Exchange. On the assumption that power prices and natural gas prices have a cointegration relationship, as tested and supported by previous studies, the short-term deviation from the long-term equilibrium is regarded as an arbitrage opportunity. The results of the spark-spread trading simulations using historical data from 2 January 2014 to 29 December 2017 show about 30% yield at maximum. This study shows the possibility of generating earnings in energy futures market. Full article
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2018

Jump to: 2022, 2021, 2020, 2019

Article
Assessment of Upstream Petroleum Fiscal Regimes in Myanmar
J. Risk Financial Manag. 2018, 11(4), 85; https://doi.org/10.3390/jrfm11040085 - 01 Dec 2018
Cited by 3 | Viewed by 2068
Abstract
This study aims to assess Myanmar’s upstream petroleum fiscal regimes by applying comprehensive indicators to rank the level of attractiveness of Myanmar. The indicators include government take (GT), front loading index (FLI), and composite score (CS). The decision maker’s attitude for GT and [...] Read more.
This study aims to assess Myanmar’s upstream petroleum fiscal regimes by applying comprehensive indicators to rank the level of attractiveness of Myanmar. The indicators include government take (GT), front loading index (FLI), and composite score (CS). The decision maker’s attitude for GT and FLI were considered in CS linear weighting method in ranking the fiscal terms attractiveness. The results showed that Myanmar’s upstream petroleum fiscal regime has low attraction compared to its competing countries from the investor’s point of view, both in terms of the risk to the investor in the earlier part of the project and in terms of evaluation with or without the time value of money. Also, royalty and cost recovery were identified to have an impact on the attractiveness rank of petroleum fiscal regime in Myanmar. Therefore, Myanmar should consider improving its fiscal regimes that are not neutral—particularly, royalty, tax, profit split, and cost recovery—for a favorable investment climate. Full article
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Article
Best Fitting Fat Tail Distribution for the Volatilities of Energy Futures: Gev, Gat and Stable Distributions in GARCH and APARCH Models
J. Risk Financial Manag. 2018, 11(2), 30; https://doi.org/10.3390/jrfm11020030 - 09 Jun 2018
Cited by 4 | Viewed by 2149
Abstract
Precise modeling and forecasting of the volatility of energy futures is vital to structuring trading strategies in spot markets for risk managers. Capturing conditional distribution, fat tails and price spikes properly is crucial to the correct measurement of risk. This paper is an [...] Read more.
Precise modeling and forecasting of the volatility of energy futures is vital to structuring trading strategies in spot markets for risk managers. Capturing conditional distribution, fat tails and price spikes properly is crucial to the correct measurement of risk. This paper is an attempt to model volatility of energy futures under different distributions. In empirical analysis, we estimate the volatility of Natural Gas Futures, Brent Oil Futures and Heating Oil Futures through GARCH and APARCH models under gev, gat and alpha-stable distributions. We also applied various VaR analyses, Gaussian, Historical and Modified (Cornish-Fisher) VaR, for each variable. Results suggest that the APARCH model largely outperforms the GARCH model, and gat distribution performs better in modeling fat tails in returns. Our results also indicate that the correct volatility level, in gat distribution, is higher than those suggested under normal distribution with rates of 56%, 45% and 67% for Natural Gas Futures, Brent Oil Futures and Heating Oil Futures, respectively. Implemented VaR analyses also support this conclusion. Additionally, VaR test results demonstrate that energy futures display riskier behavior than S&P 500 returns. Our findings suggest that for optimum risk management and trading strategies, risk managers should consider alternative distributions in their models. According to our results, prices in energy markets are wilder than the perception of normal distribution. In this regard, regulators and policy makers should enhance transparency and competitiveness in the energy markets to protect consumers. Full article
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